Genetic variability and correlation analysis in nigella (Nigella sativum L.) assessed in south eastern Rajasthan, India

Int.J.Curr.Microbiol.App.Sci (2019) 8(3): 1858-1864

International Journal of Current Microbiology and Applied Sciences
ISSN: 2319-7706 Volume 8 Number 03 (2019)
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Original Research Article

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Genetic Variability and Correlation Analysis in
Nigella (Nigella sativum L.) Assessed in South Eastern Rajasthan, India
Preeti Verma1*, R.K. Solanki2, Abhay Dashora3 and R.K. Kakani2
1

Agricultural Research Station, Kota (AU, Kota), Rajasthan (India)
2
ICAR-CAZRI, Jodhpur, Rajasthan (India)
3
Rajasthan College of Agriculture, MPUAT, Udaipur, Rajasthan (India)
*Corresponding author

ABSTRACT
Keywords
Nigella, Variability,
correlation, Path
analysis

Article Info
Accepted:
15 February 2019
Available Online:

10 March 2019

Nigella (Nigella sativa L.) is an important seed spice crop having high medicinal
importance. Genetic variability, correlation and path analysis was carried out in
thirteen nigella genotypes to work out the magnitude of variability for yield and
yield contributing traits and also to understand the mutual relationship among the
characters. The results revealed that primary and secondary branches per plant,
seeds per plant, capsules per plant and biological yield per plant are important
yield contributing traits having high heritability as well as strong correlation with
seed yield. Therefore, effective selection can be exercised for these traits for
realizing higher yield levels in nigella.

Introduction
Nigella (Nigella sativum L.) belonging to
family Ranunculaceae is an important minor
seed spice crop of India. Here, it is mainly
cultivated in states like Madhya Pradesh,
Bihar, Punjab and Assam. Besides India,
nigella is mainly cultivated in Pakistan, Sri
Lanka, Bangladesh, Nepal, Egypt and Iraq. It
is widely used medicinal plant throughout the
world. The seeds contain 0.5 to 1.4% essential
oil which has demand in the pharmaceutical
and perfume industry (Malhotra, 2004, Dubey
et al., 2016).

Seed spices are cultivated in large in
Rajasthan, western dry regions grow cumin
and fenugreek mainly, southern parts cultivate
fennel and humid south eastern plains of the

state have high acreage in coriander. In the
recent years, the humid south eastern plains
(Zone V) comprising of districts viz., Kota,
Baran, Bundi and Jhalawar where coriander is
mainly grown are facing adverse climatic
conditions and incidence of diseases like stem
gall has caused significant yield loss.
Therefore, the cultivators are showing
increased interest towards other crops, of
which nigella as an alternative seed spice crop

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Int.J.Curr.Microbiol.App.Sci (2019) 8(3): 1858-1864

has high potential. The area under nigella in
Rajasthan and zone V has been recorded
10157 hectares and 7677 hectares respectively
with maximum area of 7167 hectares in
Jhalawar district of the state. The total
production of nigella in Rajasthan is 8522 mt
with maximum contribution of 5734 mt from
Jhalawar district followed by Chittor during
2015-16. Therefore, the climate of south
eastern Rajasthan seems very conducive for
seed spices including nigella. Since meagre
reports are available regarding the extent of
genetic variability available in this crop and
keeping in view the importance of this

emerging crop in zone V, a study was
undertaken to have an insight about the
genetic parameters and mutual relationship
among the various yield contributing
characters
for
exploitation
in
crop
improvement programme of nigella.
Materials and Methods
The experimental material consisted of 13
diverse nigella genotypes including two
checks viz., AN–1, KKN-Sel–9, AN-S–5, ANS–7, AN–04, AN–06, AN–21, AN–22, AN–
23, AN–20, KKN-Sel–10, Pant Krishna (C)
and Azad Kalongi (C) grown in Randomized
Block Design with three replication during
rabi season at Agricultural Research Station,
Kota. In each replication, genotypes were
sown in a plot of 9.6 m2 accommodating 8
rows of 4 m length spaced 30 cm apart with an
intra row spacing of 10 cm. All the
recommended package of practices was
followed to raise a healthy crop. The
observations were recorded for days to 50 %
flowering, days to maturity, plant height (cm),
primary branches per plant, secondary
branches per plant, capsules per plant, seeds
per plant, biological yield per plant (g), seed
yield per plant (g), harvest index (%) and test

weight (g). Analysis of variance was done by
the method suggested by Panse and Sukhatme
(1967) and genotypic coefficient of variance,

heritability and genetic gain as per procedure
of Burton (1952), Burton and De Vane (1953)
and Johnson et al., (1955), respectively. The
genotypic
and
phenotypic
correlation
coefficient and the direct and indirect
contribution of various characters to yield was
calculated following the method suggested by
Al. Jibouri et al., (1958) and Dewey and Lu
(1959), respectively.
Results and Discussion
The analysis of variance revealed significant
differences among all the genotypes for most
of the traits studied; indicating presence of
significant variability in the material thereby
justifying the selection of the experimental
material. The range, mean and standard error
of mean, phenotypic coefficient of variation
(PCV), genotypic coefficient of variation
(GCV), heritability (h2) in broad sense and
genetic advance (GA) as per cent of mean for
various characters are presented in Table 1.
The range of characters indicated the existence
of variability for all the characters. The range

of variation was high for seed per plant
followed by plant height and harvest index.
The phenotypic coefficient of variation (PCV)
were higher than genotypic coefficient of
variation (GCV) for the traits studied which is
an indicator of additive effect of environment
on the expression of the trait. The estimates of
PCV and GCV indicated the existence of
fairly high degree of variability for seed yield
per plant and biological yield per plant.
Secondary branches per plant, harvest index,
capsules per plant, primary branches per plant
and test weight showed moderate estimates of
GCV and PCV.
The seed yield per plant showed the higher
PCV value of 52.43 per cent in comparison to
GCV of 51.52 % suggesting less
environmental influence on this character,
which was confirmed by its high heritability.
The difference between PCV and GCV was

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Int.J.Curr.Microbiol.App.Sci (2019) 8(3): 1858-1864

minimum for seed yield per plant, biological
yield per plant, harvest index, capsule per
plant suggesting that these traits were least
affected by environment. This observations

drawn support from the high value of
heritability recorded for these traits. In
corollary to high heritability estimates, high
estimates of genetic advance as per cent of
mean was observed for seed yield per plant,
biological yield per plant, harvest index and
capsule per plant indicating predominance of
additive gene effects for these traits.
The highest GCV and PCV were observed for
the characters biological yield and seed yield.
The number of secondary branches, harvest
index, capsules per plant, primary branches
and test weight showed moderate estimates of
GCV and PCV while the low estimates were
observed for days to maturity and days to 50
percent flowering, plant height and seeds per
plant.
The highest heritability estimates were found
for biological yield, seed yield per plant,
number of capsules per plant, harvest index,
days to flowering, test weight and plant
height. The characters like days to maturity,
number of primary and secondary branches
and seeds per plant showed moderate
estimates of heritability. This implies that
selection can be exercised for these traits as
they are less influenced by the environment.
The genetic advance was highest for seeds per
plant followed by harvest index, plant height
and days to 50 percent flowering. Low

estimates of genetic advance were observed
for rest of the traits. Genetic gain was highest
for seed yield and biological yield and lowest
for days to maturity and days to 50%
flowering.
The phenotypic and genotypic correlation
among the yield and yield components in
nigella are presented in Table 2. Significant

correlation of characters suggested that there
is much scope for direct and indirect selection
for further improvement. In general, the
estimates of genotypic correlation coefficient
were higher than their corresponding
phenotypic ones thereby suggesting strong
inherent association among the characters
studied.
In the present investigation, seed yield showed
positive correlation with all the yield
contributing traits but highly significant
positive correlation with biological yield,
capsules per plant, number of primary and
secondary branches per plant and seeds per
plant. Therefore, these characters should be
considered while making selection for yield
improvement in nigella. Similar results were
reported by Salamati and Zeinali (2013),
Maryam and Mohammad (2014) and Fufa
(2016). With respect to the interrelationships
among the different traits, plant height had

significant positive correlation with primary
and secondary branches per plant, capsules per
plant, seeds per plant and biological yield. The
days to 50 percent flowering showed
significant positive correlation with days to
maturity while number of primary branches
showed significant positive correlation with
secondary branches per plant, capsules per
plant, seeds per plant and biological yield per
plant. Capsules per plant had significant
positive correlation with number of seeds per
plant and biological yield. The correlation of
seeds per plant with biological yield and
harvest index was also significantly positive.
The results of present investigation on path
coefficient analysis as presented in Table 3
revealed that biological yield per plant had
highest direct effect on seed yield per plant.
The direct effects of harvest index and
primary branches per plant were also positive
and high whereas, the number of capsules per
plant, days to maturity and test weight had low
negative direct effect.

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Int.J.Curr.Microbiol.App.Sci (2019) 8(3): 1858-1864

Table.1 Range, mean, phenotypic and genotypic coefficient of variation, heritability and genetic advance as per cent of mean for

various characters in thirteen genotypes of nigella
Characters
Days to 50% flowering
Days to maturity
Plant height (cm)
Primary branches per plant
Secondary branches per plant
Capsules per plant
Seeds per plant
Biological yield per plant (g)
Seed yield per plant (g)
Harvest index (%)
Test weight (g)

Range

Mean+SE

PCV (%)

GCV (%)

h²(%)

95.97-109.00
142.67-149.00
52.00-75.90
2.60-4.90
1.47-6.10
4.20-11.20

194.50-297.20
1.39-6.24
0.27-1.87
13.54-36.63
1.20-2.27

98.95+0.81
145.28+0.82
67.41+1.58
3.62+0.34
3.76+0.56
7.45+0.30
242.89+16.71
2.88+0.13
0.77+0.04
27.23+1.145
1.76+0.07

4.17
1.52
9.60
24.21
37.97
26.10
16.21
45.18
52.43
26.45
18.61

3.92
1.17
8.71
17.74
27.96
25.12
11.00
44.53
51.52
25.40
17.10

88.33
58.81
82.20
53.74
54.22
92.68
46.00
97.15
96.58
92.28
84.42

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GA as %
of mean
7.59
1.85

16.26
26.80
42.41
49.83
15.36
90.41
104.30
50.27
32.36


Int.J.Curr.Microbiol.App.Sci (2019) 8(3): 1858-1864

Table.2 Genotypic and phenotypic (rg and rp) correlation coefficients among different characters in nigella
Character

Days to 50%
flowering
Days to maturity
Plant height
Primary branches
per plant
Secondary
branches per
plant
Capsules per
plant
Seeds per plant
Biological yield
per plant

Seed yield per
plant
Harvest index
Test weight

rg
rp
rg
rp
rg
rp
rg
rp
rg
rp

Days to
50%
flowering
1.00
1.00

Days to
maturit
y
0.97**
0.72**
1.00
1.00

Plant
height
0.11
0.09
0.29
0.16
1.00
1.00

Primary Secondary
branches branches
per plant per plant
0.02
0.16
0.06
0.16
0.24
0.51
0.21
0.36
0.62*
0.66*
0.33
0.49
1.00
0.91**
1.00
0.79**
1.00
1.00

rg
rp
rg
rp
rg
rp
rg
rp
rg
rp
rg
rp

Capsules
per plant
0.11
0.1
0.36
0.35
0.67*
0.59*
0.96**
0.73**
1.05
0.79**
1.00
1.00

1862

Seeds
per
plant
0.13
0.02
0.12
0.2
0.59*
0.38
0.58*
0.63*
0.40
0.5

Biological
yield per
plant
0.04
0.04
0.31
0.27
0.58*
0.49
0.95**
0.75**
1.01
0.78**

Seed yield

per plant

Harvest
index

0.09
0.09
0.42
0.34
0.51
0.45
0.80**
0.63*
0.86**
0.66*

0.13
0.12
0.31
0.19
0.03
0.05
0.09
0.08
0.02
0.02

0.61*
0.46
1.00

1.00

0.88**
0.84**
0.56*
0.42
1.00
1.00

0.83**
0.79**
0.89**
0.61*
0.85**
0.84**
1.00
1.00

0.11
0.08
0.71**
0.41
0.14
0.15
0.38
0.38
1.00
1.00

Test

weigh
t
0.08
0.09
0.48
0.29
0.38
0.28
0.27
0.3
0.37
0.35
0.20
0.2
0.11
0.18
0.31
0.3
0.19
0.19
0.08
0.08
1.00
1.00


Int.J.Curr.Microbiol.App.Sci (2019) 8(3): 1858-1864

Table.3 Direct and indirect effect of different characters on seed yield in nigella
Character

Days to 50% flowering
Days to maturity
Plant height
Primary branches
per plant
Secondary branches per
plant
Capsules per plant
Seeds per plant
Biological yield per plant
Harvest index
Test weight

Days to
50%
flowering

Days to
maturity

Plant
height

Primary Secondar
branches
y
per plant branches
per plant
0.00

0.01
0.03
0.02
0.08
0.03
0.13
0.04

0.05
0.04
0.00
0.00

-0.03
-0.03
-0.01
-0.01

0.00
0.01
0.02
0.01

0.01

-0.02

0.01

0.11

0.00
0.01
0.00
0.01
0.00

-0.01
-0.00
-0.01
-0.01
-0.02

0.01
0.01
0.01
0.00
0.01

0.12
0.07
0.12
-0.01
0.03

Capsules
per plant

Seeds
per plant

Biological
yield per
plant

Harves
t index

-0.04
-0.12
-0.22
-0.31

-0.00
0.00
0.01
0.01

0.04
0.32
0.61
1.00

0.07
0.17
0.02
-0.05

-0.01
-0.03

-0.03
-0.02

0.09
0.42
0.51
0.80**

0.05

-0.34

0.01

1.07

-0.01

-0.03

0.86**

0.05
0.02
0.05
-0.00
0.02

-0.33
-0.20

-0.29
-0.04
-0.07

0.01
0.01
0.01
0.01
0.00

0.93
0.60
1.06
-0.15
0.33

0.06
0.40
-0.08
0.56
-0.04

-0.01
-0.01
-0.02
0.01
-0.07

0.83**
0.89**

0.85**
0.38
0.19

1863

Test
R with
weigh seed yield
t
per plant


Int.J.Curr.Microbiol.App.Sci (2019) 8(3): 1858-1864

In conclusion, the present study indicated that
selection can be exercised for traits like number
of primary and secondary branches, number of
seeds and capsules per plant and biological
yield owing to their high heritability and strong
correlation with seed yield as well as significant
positive inter-correlation between themselves
and high positive direct effect. It is concluded
that simultaneous improvement of these traits
by selection will improve the seed yield of
nigella. Besides this, based on their mean
performance, the genotypes KKN- Sel - 9 and
AN-21 can be used as suitable parents for
breeding high yielding, dwarf and early
maturing varieties.

Acknowledgement
The first author gratefully acknowledges the
support provided by Director, National
Research Centre on Seed Spices, Ajmer and
Project Coordinator, AICRP on Spices, Calicut
(Kerala).
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How to cite this article:
Preeti Verma, R.K. Solanki, Abhay Dashora and Kakani, R.K. 2019. Genetic Variability and
Correlation Analysis in Nigella (Nigella sativum L.) Assessed in South Eastern Rajasthan.
Int.J.Curr.Microbiol.App.Sci. 8(03): 1858-1864. doi: />
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